87 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions in Netherlands
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: 12 September 2025 Apply now Are you a data scientist interested in designing and implementing process-informed machine learning and uncertainties quantification methods? Join us as a postdoc and work
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partners to reduce CO2 emissions in steel production using machine learning. You can find more information here . You will work on a theoretical and an applied project on data-enhanced physical reduced order
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-based knowledge with machine learning. You will work closely with the Utrecht University team and OpenGeoHub together with other project partners, to develop and implement surrogate and hybrid modelling
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Internet Exchange (AMS-IX), and the Faculty of Science of the University of Amsterdam. About Research group The CWI Machine Learning research group focuses on how computer programs can learn from and
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. Qualifications We are looking for a candidate with A PhD in Computer Science, Operations Research, Applied Mathematics, Mathematics, Engineering, or a related discipline. Strong programming experience, for example
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assessment. You will be provided with access to various engineering and computation toolsets along with the high-performance computer. A good background in numerical methods and computational platforms is
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(UQ) for machine learning and its validation. Your areas of research will be chosen based on both your own expert judgement and insight into trends and developments and on team requirements to ensure
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required in the organization of the logistics operations of educational processes to achieve a high quality situation where any learner at any time based on their own learning speed, level and ambition can
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Employment 0.8 - 1.0 FTE Gross monthly salary € 4,728 - € 6,433 Required background PhD Organizational unit Faculty of Philosophy, Theology and Religious Studies Application deadline 10 August 2025
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with a PhD in Human-Computer Interaction, Remote Sensing, Geo-Information Science, Cognitive Science, or a closely related field. The ideal applicant possesses a strong technical foundation, as